• Title/Summary/Keyword: Linguistic Model

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Fuzzy GMDH Model and Its Application to the Sewage Treatment Process (퍼지 GMDH 모델과 하수처리공정에의 응용)

  • 노석범;오성권;황형수;박희순
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1995.10b
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    • pp.153-158
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    • 1995
  • In this paper, A new design method of fuzzy modeling is presented for the model identification of nonlinear complex systems. The proposed fuzzy GMDH modeling implements system structure and parameter identification using GMDH(Group Method of Data Handling) algorithm and linguistic fuzzy implication rules from input and output data of processes. In order to identify premise structure and parameter of fuzzy implication rules, GMDH algorithm and fuzzy reasoning method are used and the least square method is utilized for the identification of optimum consequence parameters. Time series data for gas furnaceare those for sewage treatment process are used for the purpose of evaluating the performance of the proposed fuzzy GMDH modeling. The results show that the proposed method can produce the fuzzy model with higher accuracy than other works achieved previously.

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Alternating the Non-Alternate: A Probabilistic Approach to Dative Alternation

  • Choi Hye-Won
    • Language and Information
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    • v.9 no.1
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    • pp.51-68
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    • 2005
  • This paper proposes an informational approach to the dative alternation in English following up on the Stochastic Optimality- Theoretic (OT) model by Bresnan and Nikitina (2003). While Bresnan and Nikitina's stochastic OT model resolves the crucial problem of 'gradience' unavoidably implicated in variation phenomena by applying the notion of probability to linguistic problems, it fails to account for the details of the unusually alternating examples, which normally would not alternate. More importantly, it fails to capture the focus effect involved in the alternation. This paper has worked out all the problematic examples by modifying the Bresnan and Nikitina model. This new account captures not only the unusual behavior of the less-alternating verbs and idioms but also the special focus effect of the common alternating verbs.

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Image Understanding for Visual Dialog

  • Cho, Yeongsu;Kim, Incheol
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1171-1178
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    • 2019
  • This study proposes a deep neural network model based on an encoder-decoder structure for visual dialogs. Ongoing linguistic understanding of the dialog history and context is important to generate correct answers to questions in visual dialogs followed by questions and answers regarding images. Nevertheless, in many cases, a visual understanding that can identify scenes or object attributes contained in images is beneficial. Hence, in the proposed model, by employing a separate person detector and an attribute recognizer in addition to visual features extracted from the entire input image at the encoding stage using a convolutional neural network, we emphasize attributes, such as gender, age, and dress concept of the people in the corresponding image and use them to generate answers. The results of the experiments conducted using VisDial v0.9, a large benchmark dataset, confirmed that the proposed model performed well.

A Language Model and Clue based Machine Learning Method for Discovering Technology Trends from Patent Text (특허 문서 텍스트로부터의 기술 트렌드 탐지를 위한 언어 모델 및 단서 기반 기계학습 방법)

  • Tian, Yingshi;Kim, Young-Ho;Jeong, Yoon-Jae;Ryu, Ji-Hee;Myaeng, Sung-Hyon
    • Journal of KIISE:Software and Applications
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    • v.36 no.5
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    • pp.420-429
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    • 2009
  • Patent text is a rich source for discovering technological trends. In order to automate such a discovery process, we attempt to identify phrases corresponding to the problem and its solution method which together form a technology. Problem and solution phrases are identified by a SVM classifier using features based on a combination of a language modeling approach and linguistic clues. Based on the occurrence statistics of the phrases, we identify the time span of each problem and solution and finally generate a trend. Based on our experiment, we show that the proposed semantic phrase identification method is promising with its accuracy being 77% in R-precision. We also show that the unsupervised method for discovering technological trends is meaningful.

The Effect of Characteristics of Social Intelligence Robots on Satisfaction and Intention to Use: Focused on User of Single Person Households (소셜 지능로봇의 특성이 만족과 사용의도에 미치는 영향: 1인 가구 소셜 지능로봇 사용자를 중심으로)

  • Jeon, Gyuri;Lee, Chaehyun;Jung, Sungmi;Choi, Jeongil
    • Journal of Korean Society for Quality Management
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    • v.52 no.1
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    • pp.95-113
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    • 2024
  • Purpose: This study focused on the societal changes associated with the entry into an ultra-aged society and the increase in single-person households. The core objective of this research is to investigate how social intelligent robots can bring about positive changes in the lives of individuals in single-person households and how such changes influence user satisfaction and the intention to use these robots. Methods: The study employed a cross-sectional analysis using a structural equation model. A survey designed to assess the impact of social intelligent robots' characteristics, such as perceived encouragement, empathy, presence, appearance, and attachment, on user satisfaction and usage intentions was conducted. Data were collected from a total of 335 users and analyzed using the structural equation model. Results: In the characteristics of social intelligent robots for single-person households, it was found that empathy, presence, and attachment significantly influenced satisfaction, while perceived encouragement, empathy, and attachment significantly influenced usage intentions. The research results indicate differences between enhancing user satisfaction and increasing the intention to use social intelligent robots. The findings suggest the essential need for a user-centric approach in the design and development of social intelligent robots. Additionally, it was observed that emotional support plays a crucial role in users' experiences with social intelligent robots. Conclusion: This study verified the impact of social intelligent robots on satisfaction and usage intentions based on users' experiences. It examined the influence of linguistic, visual, and personal characteristics of robots on user experiences, providing insights into how technological and human aspects of social intelligent robots interact to shape user satisfaction and usage intentions. Consequently, the study confirmed that social intelligent robots can bring positive changes to human life, emphasizing the necessity for the advancement of robot technology in a human-centric direction.

Creation of the Conversion Table from Hangeul to the Roman Alphabet

  • Kim, Kyoung-Jing;Rhee, Sang-Burm
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.321-324
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    • 2002
  • For a rule-based conversion of Hangout into the Roman alphabet rather than a word-for-word conversion, one must come up with a faultless model for the Korean standard pronunciation rules, which are the basis of the Romanization. It is on this foundation that the Korean-Roman alphabet conversion table can be created. For linguistic modeling using PetriNet, modeling boundary and notation of modeling can be defined. In order to describe PetriNet, which is a dynamic modeling tool, as a static one, one can model the standard Korean pronunciation rules and the Hangout-Roman alphabet notation by conversion into incident matrix Thus, this research attempts to develop a mathematical modeling tool for a natural language using PetriNet, and create a Korean-Roman alphabet conversion table.

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A Knowledge-Based Linguistic Approach for Researcher-Selection (학술전문가 선정을 위한 지식 기반 언어적 접근)

  • Lim, Joon-Shik
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.6
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    • pp.549-553
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    • 2002
  • This paper develops knowledge-based multiple fuzzy rules for researcher-selection by automatic ranking process. Inference rules for researcher-selection are created, then the multiple fuzzy rule system with max-min inference is applied. The way to handle for selection standards according to a certain criteria in dynamic manner, is also suggested in a simulation model. The model offers automatic, fair, and trust decision for researcher-selection processing.

Adaptation of Clustering Method to FNN for Performance Improvement (FNN 성능개선을 위한 클러스터링기법의 적용)

  • 최재호;박춘성;오성권;안태천
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.10a
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    • pp.135-138
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    • 1997
  • In this paper, we proposed effective modeling method to nonlinear complex system. Fuzzy Neural Network(FNN) was used as basic model. FNN was fused of Fuzzy Inference which has linguistic property and Neural Network which has learning ability and high tolerence level. This paper, we used FNN which was proposed by Yamakawa. The FNN used Simple Inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. This structure has better property than other structure at learning speed and convergence ability. But it has difficulty at definition of membership function. We used Hard c-Mean method to overcome this difficulty. To evaluate proposed method. We applied the proposed method to waste water treatment process. We obtained better performance than conventional model.

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Question-Centered Creativity Development Mediated by Design Artifacts (디자인 인공물을 매개로한 질문 중심의 창의성 개발)

  • Kwon, Sunggyu
    • Journal of Engineering Education Research
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    • v.23 no.2
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    • pp.3-13
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    • 2020
  • Key objective of cornerstone design is that students are able to experience developing creative design concepts through team activities, but the objective is hard to achieve. Based on a study of research materials, this paper asserts that the possibilities of creative problem solving can be promoted in question-centering ideation model if design artifacts are represented in some forms that could invoke design thinking and then the solution space is appropriately established. In particular, design problem on which divergent questions are asked should be explored and defined so that it can be a linguistic artifact represented by various visual aids. It is recommended that curriculum is modified so that students can experience creative conceptual design.

A Study on Idle Speed Control Using Fuzzy Logic (퍼지 논리를 이용한 공회전 속도 제어에 관한 연구)

  • Ko, D.W.;Lee, Y.N.;Lee, J.K.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.2 no.5
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    • pp.23-29
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    • 1994
  • The design procedure for fuzzy logic controller depends on the expert's knowledge or trial and error. Moreover, it is very difficult to guarantee the stability and robustness of the system due to the linguistic expression of fuzzy control. However, fuzzy logic control has succeeded in many control problems that the conventional control theory has difficulties to deal with. As a result, this control theory is applied to the engine control system which a mathematical model is difficult. In this study, the fuzzy logic is applied to obtain the gain of PI control at idle speed control system, and a simple engine model is developed in order to perform simulation. Experimental results show that the response to reach the target engine speed at idle speed control system is improved by adopting the gain obtained with fuzzy logic.

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